Augmented Reality (AR) is a subset of Mixed Reality (MR) that enables seamless integration of real-world environment and computer-generated objects in real time. AR may be used in many applications to visualize invisible data, signals, and patters and allow for a user to control the same.
Recent advances in hardware and software for mobile computing have boosted the ubiquity of AR and brought about many emerging applications, not limited to only vision but also encompassing all other senses such as touch and hearing. However, AR has not found many applications in the context of wireless connectivity, mainly due to the difficulty of sensing and observing high-speed wireless signals in real time. AR may be employed to visualize signals emanating from wireless routers and distant cell towers, albeit using historical data and not updating live.
Wireless research may be hindered by the fact that radio frequency (RF) electromagnetic signals are invisible and therefore hard to visualize. Without a physically intuitive way to visualize signals as they propagate, wireless transmissions often go unaccounted for, and an “observer” must rely on mathematical analyses or after-the-fact observations to gain a better understanding of wireless network dynamics. There is a need for dynamic visualization of antennas' radiation patterns and beam directions in real time. Such insights may be particularly helpful in algorithmic verification and interpretation of experimental results, especially in mobility-based experiments.
The radiation pattern of an antenna is traditionally measured in an anechoic chamber through an extensive process using highly specialized equipment. Alternatively, simulated three-dimensional polar plots of antenna gains can be generated in domain-specific software such as HFSS from Ansys. While these plots offer a level of visualization of antenna performance, they exist solely in software and are not linked to the radio platforms on which antennas operate. To make matters worse, reconfigurable antennas can assume a number of different radiation patterns, selectable on the fly by the underlying cognitive radio. As a result, in cognitive radio networks enabled by reconfigurable antennas, there exists a disconnect between the available radiation patterns and their effects on network performance.